Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden

Background SARS-CoV-2 variants of concern, such as Omicron (B.1.1.529), continue to emerge. Assessing the impact of their potential viral properties on the probability of future transmission dominance and public health burden is fundamental in guiding ongoing COVID-19 control strategies. Methods With an individual-based transmission model, OpenCOVID, we simulated three viral properties; infectivity, severity, and immune-evading ability, all relative to the Delta variant, to identify thresholds for Omicron’s or any emerging VOC’s potential future dominance, impact on public health, and risk to health systems. We further identify for which combinations of viral properties current interventions would be sufficient to control transmission. Results We show that, with first-generation SARS-CoV-2 vaccines and limited physical distancing in place, a VOC’s potential future dominance is primarily driven by its infectivity, which does not always lead to an increased public health burden. However, we also show that highly immune-evading variants that become dominant, even in the case of reduced variant severity, would likely require alternative measures to avoid strain on health systems, such as strengthened physical distancing measures, novel treatments, and second-generation vaccines. Expanded vaccination, that includes a booster dose for adults and child vaccination strategies, is projected to have the biggest public health benefit for a highly infective, highly severe VOC with low immune-evading capacity. Conclusions These findings provide quantitative guidance to decision-makers at a critical time while Omicron’s properties are being assessed and preparedness for emerging VOCs is eminent. We emphasise the importance of both genomic and population epidemiological surveillance.


Supplementary
. Overview of two vaccination scenarios. No future vaccination, and expanded vaccination through third-dose in adults (six months after second-dose) and scale up in 5-17-year-olds with first-generation vaccines. Additional details are provided in section 2.2 'Vaccine rollout'.

Model initialisation
All model simulations were designed to be pseudo-representative of a general Western European setting at the beginning of December 2021. We assume 30% of the population have been previously infected with SARS-CoV-2 over a 630-day period (representing epidemic outbreak in Europe in March 2020). The fraction that was both previously infected and vaccinated prior to the emergence of the Omicron variant was age-dependent and ranged from 3% in 10-20-year-olds to 30% in 80-90-year-olds (see section 2.2 'Vaccine rollout' for further details on vaccination rates prior to the Omicron's emergence). We assume the effective reproduction number on 1 December 2021 is equal to 1.2. This represents increasing case numbers across Europe at the start of the winter period, prior to the emergence of Omicron.
The average number of daily contacts required to achieve an initial effective reproduction number of 1.2 inherently considers any non-pharmaceutical interventions in place at the beginning of the winter period in Europe prior to the emergence of Omicron. Seasonality is assumed to follow a cosine function, with a peak in seasonal infectivity occurring 6 weeks from model initialisation (representing mid-winter, Supplementary Figure 2).

Vaccine-induced immunity profile
We model an interval of 28 days between the first and second dose, and a maximum of 95% vaccine efficacy to be reached 14 days after the second dose (increasing with a sigmoidal curve). We assume that 90% of vaccination effect is transmission blocking (i.e. a 90% reduced probability to become infected after being exposed). We assume vaccinated individuals will always be administered two doses and assume that 95% of those vaccinated with doses one and two will accept a third-dose. Third-doses are administered 6 months after the second dose, after which the maximum vaccine efficacy of 95% is again reached 14 days after the last dose has been administered. One month after the last dose, immunity starts waning linearly to zero over 335 days 2,3 . The left panel of Supplementary Figure 1, titled 'immunity from vaccination', provides a schematic overview of the waning immunity pattern after vaccination.

Infection-induced immunity profile
After recovering from infection with SARS-CoV-2, individuals develop naturally acquired immunity with a maximum level of 90% reduced susceptibility which they maintain for a month, after which their immunity wanes linearly to zero over a period of 335 days 2,3 . The level of immunity is the reverse of the susceptibility of the individual, which thus increases over time.
The Delta variant is assumed not to be immune evading, therefore immunity following infection from Delta and Omicron provides a similar risk of infection when exposed to Delta. The right panel of Supplementary Figure 1, titled 'immunity from natural infection', provides a schematic overview of the waning immunity pattern after natural infection.

Effect of variant properties and vaccination on prognosis
The individual's prognosis depends on multiple factors including age, vaccine status, comorbidity, and variant severity. The probabilities of 1) a symptomatic case developing severe disease, 2) a severe case becoming critical, and 3) a critical case ultimately leading to death, are all defined as functions for the above-mentioned factors. For this study, we use probabilities reported in 4 , updated to represent the additional risk of hospitalisation from infection with VOC Delta (B.1.617.2) 5-7 . In additional to age-related risk, the probability that an infected individual will develop severe symptoms is also scaled by the severity factor of the viral variant exposed to.
In this study we use a severity factor of 1 for VOC Delta (B.1.617.2), and consider a range of potential relative severity factors for VOC Omicron (B.1.1.529) between 0 and 2. That is, a variant that has 0%-200% severity of Delta. For vaccinated individuals that become infected (noting that the transmission-blocking action of the vaccine reduces the probability of infection), the probability of developing severe disease is reduced by the severity or diseaseblocking property of the vaccine. The level to which the probability of severe disease is reduced is dependent upon the level of immunity at the time of infection.
Vaccine-induced immunity is assumed to wane over time and can be further decreased if